The hyper-enhanced local positioning system (HELPS) has been proposed to overcome the accuracy limitations of conventional technologies for emergency positioning systems. With HELPS, first responders use signal measurement equipment (SME), which is a portable device to measure the uplink signal from a mobile phone owned by an emergency caller. In this paper, the detection range of SME is investigated.

Channel-adaptive random access is proposed to reduce the required transmission power for random access in TDD-based wireless systems. With channel-adaptive random access, a remote station measures the channel state of the downlink, estimates the channel state of the corresponding uplink based on the downlink measurement, and transmits a random access packet only when the channel satisfies a predetermined transmission condition. Thus, transmission is delayed until the channel satisfies the transmission condition. With conventional channel-adaptive random access, a remote station continuously measures the channel state to check if the channel satisfies the transmission condition, which consumes a large amount of power. In this paper, we propose a discontinuous channel measurement scheme for channel-adaptive random access to reduce the power consumption. The performance of the proposed method is investigated in terms of the detection performance of a random access packet, transmission delay, and the power consumption of the receiver.

Channel-adaptive random access can reduce the power required for successful random access transmission in a TDD-based wireless system. With channel-adaptive random access, transmission of a random access packet is delayed until a predefined channel condition is satisfied. The performance of channel-adaptive random access has been investigated with suboptimal power allocations including constant and channel inversion power allocations. However, the optimal power allocation has not been studied for channel-adaptive random access. In this paper, the optimum power allocation is derived for channel-adaptive random access, especially considering the detection performance of a random access preamble. Some important properties are investigated for the optimum power allocation. Numerical results compare the performances of the optimum and the suboptimal power allocations.

In this letter, for general fading distributions, it is rigorously shown that the water-filling power allocation function converges pointwise to the function which allocates fixed power to all non-zero channel gain states, as SNR approaches infinity. The convergence speed of the water-filling power allocation is also investigated.

In this letter, a numerically efficient algorithm is presented to compute the performance upper bounds for terminated convolutional codes based on a modified trellis diagram. A weight enumerator of one variable is defined with a new set of coefficients. The coefficients of the weight enumerator are shown to form a semiring.

In coded OFDM systems, the transmission power of each subchannel is the same. In this letter, a power optimization scheme is presented to minimize FER or BER of a coded OFDM system under constant transmission power constraint. The power optimization is shown to be a convex optimization problem.

In practical applications, some coded symbols are unequally punctured for rate matching of terminated convolutional codes. In this letter, performance upper bounds are proposed for a terminated convolutional code punctured with an arbitrary pattern. To obtain the upper bounds, a weight enumerator is defined to represent the relation between the Hamming weight of the coded outputs and that of the selected input information bits. A method is presented to compute the weight enumerator based on a modified trellis diagram. Simulation and numerical analysis show that the proposed bounds are tight to the performance of terminated convolutional codes.

In this paper, we present performance upper bounds for convolutional codes terminated with finite input sequence. To obtain the upper bounds, we define a generalized weight enumerator representing the relation between the Hamming distance of the coded output and the Hamming distance of selected input bits of the code. The upper bounds on frame error rate (FER) and average bit error rate (BER) of selected bits are obtained from the generalized weight enumerators. We present a low complexity method to compute the weight enumerator of terminated convolutional codes based on a modified trellis. We also present a generalized weight enumerator of single error event to provide tighter performance upper bounds by removing codewords composed of multiple error events from the weight enumerator.